examples/src/main/java/org/apache/spark/examples/streaming/JavaStatefulNetworkWordCount.java
<gh_stars>0/*
 * Licensed to the Apache Software Foundation (ASF) under one or more
 * contributor license agreements.  See the NOTICE file distributed with
 * this work for additional information regarding copyright ownership.
 * The ASF licenses this file to You under the Apache License, Version 2.0
 * (the "License"); you may not use this file except in compliance with
 * the License.  You may obtain a copy of the License at
 *
 *    http://www.apache.org/licenses/LICENSE-2.0
 *
 * Unless required by applicable law or agreed to in writing, software
 * distributed under the License is distributed on an "AS IS" BASIS,
 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 * See the License for the specific language governing permissions and
 * limitations under the License.
 */

package org.apache.spark.examples.streaming;

import java.util.Arrays;
import java.util.List;
import java.util.regex.Pattern;

import scala.Tuple2;

import org.apache.spark.SparkConf;
import org.apache.spark.api.java.function.*;
import org.apache.spark.api.java.JavaPairRDD;
import org.apache.spark.api.java.Optional;
import org.apache.spark.api.java.StorageLevels;
import org.apache.spark.streaming.Durations;
import org.apache.spark.streaming.State;
import org.apache.spark.streaming.StateSpec;
import org.apache.spark.streaming.api.java.*;

/**
 * Counts words cumulatively in UTF8 encoded, '\n' delimited text received from the network every
 * second starting with initial value of word count.
 * Usage: JavaStatefulNetworkWordCount <hostname> <port>
 * <hostname> and <port> describe the TCP server that Spark Streaming would connect to receive
 * data.
 * <p>
 * To run this on your local machine, you need to first run a Netcat server
 * `$ nc -lk 9999`
 * and then run the example
 * `$ bin/run-example
 * org.apache.spark.examples.streaming.JavaStatefulNetworkWordCount localhost 9999`
 */
public class JavaStatefulNetworkWordCount {
  private static final Pattern SPACE = Pattern.compile(" ");

  public static void main(String[] args) throws Exception {
    if (args.length < 2) {
      System.err.println("Usage: JavaStatefulNetworkWordCount <hostname> <port>");
      System.exit(1);
    }

    StreamingExamples.setStreamingLogLevels();

    // Create the context with a 1 second batch size
    SparkConf sparkConf = new SparkConf().setAppName("JavaStatefulNetworkWordCount");
    JavaStreamingContext ssc = new JavaStreamingContext(sparkConf, Durations.seconds(1));
    ssc.checkpoint(".");

    // Initial state RDD input to mapWithState
    List<Tuple2<String, Integer>> tuples =
        Arrays.asList(new Tuple2<>("hello", 1), new Tuple2<>("world", 1));
    JavaPairRDD<String, Integer> initialRDD = ssc.sparkContext().parallelizePairs(tuples);

    JavaReceiverInputDStream<String> lines = ssc.socketTextStream(
            args[0], Integer.parseInt(args[1]), StorageLevels.MEMORY_AND_DISK_SER_2);

    JavaDStream<String> words = lines.flatMap(x -> Arrays.asList(SPACE.split(x)).iterator());

    JavaPairDStream<String, Integer> wordsDstream = words.mapToPair(s -> new Tuple2<>(s, 1));

    // Update the cumulative count function
    Function3<String, Optional<Integer>, State<Integer>, Tuple2<String, Integer>> mappingFunc =
        (word, one, state) -> {
          int sum = one.orElse(0) + (state.exists() ? state.get() : 0);
          Tuple2<String, Integer> output = new Tuple2<>(word, sum);
          state.update(sum);
          return output;
        };

    // DStream made of get cumulative counts that get updated in every batch
    JavaMapWithStateDStream<String, Integer, Integer, Tuple2<String, Integer>> stateDstream =
        wordsDstream.mapWithState(StateSpec.function(mappingFunc).initialState(initialRDD));

    stateDstream.print();
    ssc.start();
    ssc.awaitTermination();
  }
}
